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Public Health Performance Management Centers for Excellence Funded by CDC’s National Public Health Improvement Initiative Welcome! Monitoring Quality Improvements: Introduction to Variation Theory will begin shortly 1

Monitoring Quality Improvements: Introduction to … QI...Monitoring Quality Improvements: Introduction to Variation Theory May 8, 2013 2 ... The Quality Management Trilogy 9 Quality

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Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Welcome!

Monitoring Quality Improvements:

Introduction to Variation Theory

will begin shortly

1

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Monitoring Quality Improvements:

Introduction to Variation Theory

May 8, 2013

2

Stacy Wenzl,

Spokane Regional Health District

Megan Davis,

Washington State Dept. of Health

Public Health Performance Management Centers for Excellence 5-8-2013

Adams

Benton-Franklin

Chelan-Douglas

Clallam

Clark

Columbia

Cowlitz

Garfield

Grant

Island

Jefferson

Kitsap

Kittitas

Klickitat

Lewis

Lincoln

Northeast Tri-County Okanogan

Pacific

King

San Juan

Skagit

Skamania

Snohomish

Spokane

Pierce

Thurston

Wahkiakum Walla Walla

Whatcom

Whitman

Yakima

Grays

Harbor

Asotin

Chelan

Douglas

Ferry Stevens

Pend

Oreille

Benton

Franklin

Mason

Noosack Tribe

Lummi Tribe

Upper Skagit Tribe

Sauk-Suiattle Tribe

Samish Tribe Swinomish Tribe

Stillaguamish Tribe

Snoqualmie Tribe

Muckleshoot Tribe

Puyallup Tribe

Suquamish Tribe

Makah Tribe

Lower Elwha Klallam Tribe Jamestown

S’Klallam Tribe Quileute Tribe

Hoh Tribe

Port Gamble S’Klallam

Tribe

Skokomish Tribe Quinault Tribe

Shoalwater Bay Tribe

Nisqually Tribe

Chehalis Confederated

Tribes

Confederated Tribes and Bands

Yakima Nation WA State Dept. of Health

Center for Excellence

Tacoma-Pierce County Center for Excellence

Colville Confederated

Tribes

Kalispel Tribe

Spokane Regional Health Center for Excellence

Tulalip Tribe

Tacoma-Pierce

Seattle-King County

Tacoma-Pierce Co Health Dept.

WA State Dept. of Health

Spokane Regional Health

District

County Boundaries

Washington’s Federally Recognized Tribes

Squaxin Tribe

Spokane Tribe

Which Center for Excellence Region are you located in? A. Department of Health B. Tacoma-Pierce County Health Department

C. Spokane Regional Health District D. Outside Washington State

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Learning Objectives • Upon completion participants should be

able to: – Explain why understanding variation is so

important to controlling for quality and

improving processes

– Describe how variation is demonstrated in work

processes and the impact on QI efforts

– Describe trend lines, run charts, and control

charts and their uses

– Identify examples of each chart type

– Analyze data displayed in each chart type

4

Public Health Performance Management Centers for Excellence 5-8-2013

Why is variation important?

• All activities and services are comprised of

work process- a series of steps to produce

an outcome

• All work processes have variation

• The underlying process determines

performance

• Improving work processes requires

understanding and reducing variation

5

Public Health Performance Management Centers for Excellence 5-8-2013

Process Variation

6

0

10

20

30

40

50

60

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Incidences per Month

Hmmm. Why does it vary so much?

Public Health Performance Management Centers for Excellence 5-8-2013

Sources of variation

• Methods

• Materials

• Environment

• Staff

• Measurements

• Customers

7

Which

among

these are

variable?

Which among

these are

controllable?

Public Health Performance Management Centers for Excellence 5-8-2013

POLL:

Which procedure is more likely to take

longer to complete? And why?

8

Step

1

Step

3

Step

4

Step

2

Step

1

Step

3

Step

5

Step

4

Step

2

Inputs: Inputs: A. B.

Public Health Performance Management Centers for Excellence 5-8-2013

The Quality Management Trilogy

9

Quality Planning (QP)

Quality Control (QC)

Quality Improvement

(QI)

Joseph Juran, 1950’s

Juran on Leadership for Quality, Free Press, 1989

Public Health Performance Management Centers for Excellence 5-8-2013

The Quality Management Trilogy

10

Quality Planning (QP)

Quality Control (QC)

Quality Improvement

(QI)

Joseph Juran, 1950’s

Juran on Leadership for Quality, Free Press, 1989

Process Design

Public Health Performance Management Centers for Excellence 5-8-2013

The Quality Management Trilogy

11

Quality Planning (QP)

Quality Control (QC)

Quality Improvement

(QI)

Joseph Juran, 1950’s

Juran on Leadership for Quality, Free Press, 1989

Process Control

Public Health Performance Management Centers for Excellence 5-8-2013

The Quality Management Trilogy

12

Quality Planning (QP)

Quality Control (QC)

Quality Improvement

(QI)

Joseph Juran, 1950’s

Juran on Leadership for Quality, Free Press, 1989

Process Improvement

Public Health Performance Management Centers for Excellence 5-8-2013

The Quality Trilogy (adapted from Juran Trilogy)

13

Define Opportunit

y & Stakeholde

r Needs

Design & Pilot Service or Process

Monitor Impact / Results of Service

Take Action

Sporadic

Spike

Original Zone

of Quality Control

QualityImprovement

Time

Op

eart

ion

s

Beg

in

Quality Planning

New Zone

of Quality Control

Process not Achieving

Desired Results

(An Opportunity

for Improvement)

Quality Control & Improvement (During Operations)

Model for Improvement

What are we trying

to accomplish?

How will we know that a

change is an improvement?

Act Plan

DoStudy

Public Health Performance Management Centers for Excellence 5-8-2013

The Quality Management Trilogy

14

Quality Planning (QP)

Quality Control (QC)

Quality Improvement

(QI)

Joseph Juran, 1950’s

Juran on Leadership for Quality, Free Press, 1989

Our focus today

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Process Capability and Stability

• Process Capability

– The performance level is capable of meeting customer needs and expectations within a stable process.

• Process Stability

– Whether process is in control and produces predictable results.

– Must understand variation in process.

15

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Process Capability and Stability

• Process Capability

– The performance level is capable of meeting customer needs and expectations within a stable process.

• Process Stability

– Whether process is in control and produces predictable results.

– Must understand variation in process.

16

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Process Capability • Does the process meet or exceed the

customer’s specification? (aka, expectation,

requirement, etc.)

– All the time?

– Some of the time?

– None of the time?

• If the process is not capable, controlling

existing variation will not be your first

priority

17

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Process Specifications

• May have an upper specification

– Data point less than x is good

• May have a lower specification

– Data point greater than y is good

• May have both

– Data point between x and y is good

18

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Process Capability

0

10

20

30

40

50

60

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Days to Complete Request

19

Customer

Requirement

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Process Capability

0

10

20

30

40

50

60

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Days to Complete Request

20

Customer

Requirement

No ―lower‖

specification

because no

wait is a

good thing!

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Process Capability

0

10

20

30

40

50

60

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Days to Complete Request

21

Customer

Requirement

Our Current

Performance

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Hmmm…

0

10

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60

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Days to Complete Request

22

Customer

Requirement

Our Current

Performance

If my process is not capable …

Do I care if it stable or not?

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

0

10

20

30

40

50

60

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Days to Complete Request

23

Need to

shift to a

level of

performance

that is

capable

It doesn’t matter that my process isn’t stable, it’s

not even capable!

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Process Capability and Stability

• Process Capability

– The performance level is capable of meeting customer needs and expectations within a stable process.

• Process Stability

– Whether process is in control and produces predictable results.

– Must understand variation in process.

24

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Process Capability and Stability

• Process Capability

– The performance level is capable of meeting customer needs and expectations within a stable process.

• Process Stability

– Whether process is in control and produces predictable results.

– Must understand variation in process.

25

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Why Understand Variation?

A major principle underlying quality improvement

is that any substantial improvement must come

from a change in the work process (data driven),

rather than focusing on an individual occurrence

or event (anecdotal).

• Common Causes (94%) belong to the work

process

• Special Causes (6%) are the result of fleeting or

unusual occurrences

26

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

• Sources of variation include: technology, materials, methods, culture, people, environment

• Common cause variation occurs if the process is stable— variation in data points will be random and obey a mathematical law—it is said to be in statistical control, with a large number of small sources of variation

• Reacting to random variation in a process that is stable/in statistical control, it is called tampering and leads to further complexity, increasing variation and mistakes

Stability - Understand Variation

27

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

• Special cause variation arises because of specific circumstances which are not part of the process all the time and may or may not ever recur—if the recurrence is periodic, clues to the root cause may emerge

• If variation is special, then process not stable

• Special causes should be investigated

Stability - Understand Variation

28

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Two Types of Variation

• Common Cause – Built into every

process

– Reflects a stable process because variation is predictable

– Also called random variation

– Requires changing the process to improve results

29

• Special Cause

– Not part of ―daily‖ or

―regular‖ process

– A single data point

outside control limits

OR a noticeable shift in

data points over time

– Can be improved or

avoided by addressing

this cause alone

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Stability- Understand Variation

• Failure to distinguish between common and special cause variation can be hazardous to organizational performance

• Addressing a single occurrence of common cause variation is called TAMPERING with your process

30

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Tampering If process is capable and stable …

– Want to avoid confusing expected/common cause variation

with un-expected/special cause variation

―Wait …What?‖

– Beware over interpreting a few data points (or worse one data

point) as indicating your process is deteriorating when it really

isn’t

– Managing to ―last month’s number‖ … is a ticket to tampering

– Managing to a target without a picture of process variation is a

ticket to tampering

―So?...‖

Identify the expected range of variation and limit reaction to

unexpected variation

31

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

The dangers of tampering

• At best … you waste time

and effort

• Likely introduce more

variation

• Perhaps … make things

worse

32

Public Health Performance Management Centers for Excellence 5-8-2013

Control Chart

Public Health Performance Management Centers for Excellence 5-8-2013

Acting on Variation to Ensure Stability

34

Expected or

unexpected

variation?

Unexpected

and special?

Expected or

common?

Is overall

performance

acceptable?

Search for and

eliminate

special causes

associated

with a few

data points

Yes

No

Do nothing!

Search for and

eliminate

common

causes

associated

with all data

points (i.e.

change

process/QI

Project)

(assuming process is capable)

Adapted from NDP on QI in Health Care, 1991

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

When to Improve the Process Cause of

Variation :

Common Causes Special Causes

Action Required : To change the

process (QI)

Fix or mitigate

the issue (not a QI

project)

Frequency: 94% (Deming) 6%

Who: QI team/project Managers or staff

35

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Please unmute phone or use chat window

What experiences have you encountered with variation in a work process?

Examples might be inconsistently meeting regulatory deadlines or responding to requests.

Let’s Discuss

36

Public Health Performance Management

Centers for Excellence

RUN CHARTS, TREND CHARTS

AND CONTROL CHARTS

Charts:

37

Public Health Performance Management Centers for Excellence 5-8-2013

Run Chart Elements

38

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10

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60

70

80

90

100

M1 M2 T1 T3 W1 W2 TH1 TH2 F1 F2 S1 S2 M1 M2 T1 T2 W1 W2

Samples by time unit, run, etc.

Count of individuals or average of the sample

Calculated mean from initial series of samples … at LEAST 8

Public Health Performance Management Centers for Excellence 5-8-2013

Line/Run/Trend Charts

• Indicates pattern of variation over time

• Helps avoid over-interpreting a particular

result/sample

• Can indicate expected range of random

variation (aka common cause)

• Can indicate patterns of unexpected and

attributable variation (aka special cause)

39

Public Health Performance Management Centers for Excellence 5-8-2013

Key Points for Analyzing Data

• The average by itself is not a good summary of data; use a variety of numerical summaries

• Measures of center include: Average/Mean: the total data values divided by the total number of observations Median: the middle value in the data set, half of the data value lie above, half lie below the median Mode: the most frequently occurring values in the set of data

• Use histograms to look at overall variation patterns

• Use line graphs to look at patterns over time

Public Health Performance Management Centers for Excellence 5-8-2013

0

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trial 2

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trial 16

trial 17

trial 18

trial 19

trial 20

Random and Expected: # Times Heads in 10 chance Trial

# heads

Avg

41

Public Health Performance Management Centers for Excellence 5-8-2013

Line Chart Indicators of

Unexpected/Attributable Variation

• Trends (7 points in a row in same direction)

• Shifts (7 continuous points above/below the

mean)

• Data Collection Problems/Manipulation (5

identical points in a row)

• Personal variation (alternating pattern)

42

Public Health Performance Management Centers for Excellence 5-8-2013

0

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trial 2

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trial 18

trial 19

trial 20

Trend

# heads

Avg

43

POLL At what trial number does the trend start?

A. Trial 3 B. Trial 10 C. Trial 13

Public Health Performance Management Centers for Excellence 5-8-2013

0

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trial 1

trial 2

trial 3

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Trend

# heads

Avg

44

Public Health Performance Management Centers for Excellence 5-8-2013

0

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8

9

10

trial 1 trial 2 trial 3 trial 4 trial 5 trial 6 trial 7 trial 8 trial 9 trial 10

trial 11

trial 12

trial 13

trial 14

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trial 16

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trial 18

trial 19

trial 20

Shift

# heads

Avg

45

POLL:

What trial number does the shift start?

A. Trial 3 B. Trial 11

Public Health Performance Management Centers for Excellence 5-8-2013

0

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trial 1 trial 2 trial 3 trial 4 trial 5 trial 6 trial 7 trial 8 trial 9 trial 10

trial 11

trial 12

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trial 18

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trial 20

Shift

# heads

Avg

46

POLL:

What trial number does the shift start?

A. Trial 3 B. Trial 11

Public Health Performance Management Centers for Excellence 5-8-2013

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trial 11

trial 12

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# heads

Avg

47

CHAT BOX:

What conclusions might you draw from this data?

Public Health Performance Management Centers for Excellence 5-8-2013

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trial 11

trial 12

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# heads

Avg

48

Data Collection Problems – repeat results

(data fudged?)

? ?

Public Health Performance Management Centers for Excellence 5-8-2013

0

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trial 2

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trial 20

# heads

Avg

49

CHAT BOX:

What conclusions might you draw from this data?

Public Health Performance Management Centers for Excellence 5-8-2013

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trial 20

# heads

Avg

50

Data Collection/Sampling Problems – Alternating Pattern

(Differences between staff? between shifts?

More than one process?)

Public Health Performance Management Centers for Excellence 5-8-2013

0

2

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12

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trial 11

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Capable, Random and Expected: # Days to Complete an Environmental Health Permit

A Good QI Project Candidate

51

Public Health Performance Management Centers for Excellence 5-8-2013

0

200

400

600

800

1000

1200

Nu

mb

er

of

Clin

ic V

isit

s

Month

Port Gamble S'Klallam Tribe Run Chart: Number of Clinic Visits Per Month

June 2008 - May 2010

Number of Clinic Visits

Xbar (Median)

Median = 637 visits per month

Start of Intervention

1st Staff Training 2nd Staff

Training

Public Health Performance Management Centers for Excellence 5-8-2013

0

200

400

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Jun-0

8

Jul

Aug

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Feb

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Jun

July

Aug

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Oct

Nov

Dec

Jan-1

0

Feb

Mar

Apr

May-1

0

Port Gamble S'Klallam Tribe

Control Chart with Process Shift

Number of Clinic Visits Per Month

June 2008 - May 2010 POLL:

Did the Port

Gamble

S’Klallam

intervention

aimed at

increasing

visits work?

A. Yes

B. No

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Control Charts

Same elements as a run chart plus:

• Upper/lower control limits placed a certain number of standard deviations (or practical equivalent) from the mean

• Like the mean, limits are based on initial series of samples

• Typical choice is 3 standard deviations (captures 99% of the variation from a normally distributed population)

54

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Control Chart

Public Health Performance Management Centers for Excellence 5-8-2013

Data point outside control limits

85

87.5

90

92.5

95

97.5

100

102.5

A B C D E F G H I J K L M N O

Value

Mean

UCL

LCL

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Standard Deviation

• Represented by the lowercase form of the Greek letter sigma, is a statistic that tells you how tightly the data points are clustered around the mean for a given process.

• This tells you how much variation exists. – When data points are tightly clustered around the

mean and the bell-shaped curve is steep, the standard deviation and the range of variation is small.

– When the data points are spread apart and the bell-shaped curve is flat, the standard deviation and range of the variation is great.

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Standard Deviation

• Analysts generally talk about the number of

standard deviations from the mean.

• One standard deviation in either direction of

the mean accounts for 68 percent of the data in

the group.

• Two standard deviations account for 95 percent

of it.

• Three standard deviations account for 99

percent of the data.

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Control Chart Construction

Options:

• Follow Public Health Memory Jogger II instructions, pages 36 to 51.

• Write formulas and build templates in Excel

• Buy Excel data pack add-ons (Green Belt XL, etc.)

• Download Excel templates from internet (usually free)

• Mini-tab or other stats program

• Incorporate control limits into Crystal and SQL query reports

60

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Specifications and Control Limits

• Don’t confuse them!!!

– A specification tells you how well you need

the process to perform

– A control limit is a statistical reference that

helps you distinguish between expected

results and unexpected results

– A process can be ―in control‖ but not quality

– A process can be meeting the specification

but be ―out of control‖

61

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

0

10

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60

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Days to Complete Request

62

Need to

shift to a

level of

performance

that is

capable

Need to

shift to a

level of

performance

that is

capable

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Control Charts

• Pitfalls

– Non-normal distribution such as data

collection problems, shift in data, or

alternating pattern in run chart

– Not adjusting control limits periodically

– Over Rounding

– Sampling variation

63

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Discussion

• What are situations where control charts

might be helpful in public health?

– Why?

– What would be concerns?

64

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

In Summary

• Understanding variation is crucial to

selecting appropriate work processes for

QI projects

• Responding correctly to the type of

variation, and not tampering, makes our

management and QI efforts more

effective

65

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

Review Learning Objectives • Upon completion participants should be

able to:

– Explain why understanding variation is so

important to improving processes

– Describe how variation is demonstrated in

work processes and the impact on QI efforts

– Describe trend lines, run charts, and control

charts and their uses

– Identify examples of each chart type

– Analyze data displayed in each chart type 66

Public Health Performance Management Centers for Excellence 5-8-2013

67

Additional Resources • Performance Management Centers for Excellence Web site:

www.doh.wa.gov/PHIP/perfmgmtcenters

• Public Health Memory Jogger, GOAL/QPC, 2007, www.goalqpc.com, pages 36 through 51

• Creating Control Charts in Excel instructions: http://www.ehow.com/how_5928553_create-control-charts-excel.html

• Bialek R, Duffy DL, Moran JW. The Public Health Quality Improvement Handbook. Milwaukee, WI: ASQ Quality Press; 2009

• The Improvement Guide, Langley et al. Jossey-Bass, 1996.

• Juran, J.; Juran on Leadership for Quality, Free Press, 1989

• Juran, J.; Juran on Planning for Quality, Free Press, 1988

• Mason M, Moran J, Understanding and Controlling Variation in Public Health. Journal of Public Health Management and Practice. Jan/Feb 2012; 18(1), 74–78

67

Public Health Performance Management Centers for Excellence 5-8-2013

THANKS FOR YOUR PARTICIPATION! Please complete the evaluation you

receive via email.

Join us Next Time:

July 17, 2013

“Quality Tools Training”

The contents of this presentation were selected by the author

and do not necessarily represent the official position of or

endorsement by the Centers for Disease Control and Prevention.

68

Public Health Performance Management

Centers for Excellence

Funded by CDC’s National Public Health Improvement Initiative

What questions do

you have?

69